Distributed optimal coverage control in multi-agent systems: Known and unknown environments by Mohammadhasan Faghihi (22303057)

“…The proposed approach leverages a novel cost function for optimizing the agents’ coverage and the cost function eventually aligns with the conventional Voronoi-based cost function. …”

Optimum Track to Track Fusion Using CMA-ES and LSTM Techniques by Fares, Samar

“…An objective function utilizing the covariance of the fused tracks is used by the first algorithm while a cost function based on the Kullback-Leibler (KL) divergence measure is used in the second case for training the LSTM. …”
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Multi-Target Tracking Resources Allocation Using Multi-Agent Modeling and Auction Algorithm by De Rochechouart, Maxence

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Process Targeting Of Multi-Characteristic Product Using Fuzzy Logic And Genetic Algorithm With An Interval Based Taguchi Cost Function by Mujahid, S.N.

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Process Targeting Of Multi-Characteristic Product Using Fuzzy Logic And Genetic Algorithm With An Interval Based Taguchi Cost Function by Duffuaa, S. O.

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Logarithmic spiral search based arithmetic optimization algorithm with selective mechanism and its application to functional electrical stimulation system control by Abu Zitar, Raed

Application of Red Deer Algorithm in Optimizing Complex functions by Zitar, Raed

“…The Red Deer algorithm (RDA), a recently developed population-based meta-heuristic algorithm, is examined in this paper with the optimization task of complex functions. …”
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ANT-colony optimization-direct torque control for a doubly fed induction motor : An experimental validation by Said Mahfoud (17150968)

“…The new combined ACO-DTC strategy has been studied for optimizing the gains of the PID controller by using a cost function such as Integral Square Error (ISE). …”

Guaranteed Cost Control Of A Markov Jump Linear Uncertain System UsingA Time-Multiplied Cost Function by Boukas, EK

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Guaranteed Cost Control Of A Markov Jump Linear Uncertain System Using A Time-Multiplied Cost Function by Boukas, EK

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Guaranteed Cost Control Of A Markov Jump Linear Uncertain System Using A Time-Multiplied Cost Function by Boukas, EK

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Improving the Secure Socket Layer Protocol by modifying its Authentication function by El-Kassar, A. N.

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Genetic and heuristic algorithms for regrouping service sites. (c2000) by Tabbara, Hiba

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Economic load dispatch using memetic sine cosine algorithm by Abu Zitar, Raed

“…The results show that the performance of the SCA-βHC algorithm is increased by tuning its parameters in proper value. …”
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Modified arithmetic optimization algorithm for drones measurements and tracks assignment problem by Abu Zitar, Raed

“…In particular, a new modified method based on the Arithmetic Optimization Algorithm is proposed. The optimization is applied to a formulated cost function that considers uncertainty, false alarms, and existing clutters. …”
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A hybrid of clustering and meta-heuristic algorithms to solve a p-mobile hub location–allocation problem with the depreciation cost of hub facilities by Mahdi Mokhtarzadeh (11593310)

“…Three objective functions are considered to minimize costs, noise pollutions, and the harassment caused by the establishment of a hub for people, a new objective that locates hubs in less populated areas. …”

An efficient failure-resilient mutual exclusion algorithm for distributed systems leveraging a novel zero-message overlay structure by Mouna Rabhi (17086969)

“…The overlay structure – a unique logical tree – used to control access to the critical section maintains its consistency even when nodes fail. An extensive simulation study demonstrates the viability and efficiency of the proposed algorithm under various node failure models, and relevant metrics (e.g., node queue dimension, number of exchanged messages, and number of disconnected nodes) indicate a graceful degradation in performance with decreasing number of functioning nodes. …”

Improved scatter search algorithm for predicting all-atoms protein structures using charmm22 energy model. (c2010) by Ghalayini, Iman Adnan

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STEM: spatial speech separation using twin-delayed DDPG reinforcement learning and expectation maximization by Muhammad Salman Khan (7202543)

Optimum sensors allocation for drones multi-target tracking under complex environment using improved prairie dog optimization by Abu Zitar, Raed

“…The goal is to select a set of sensors based on norms of weighted distances cost function. The norms are the Euclidean distance and the Mahalanobis distance between the drone location and the sensors. …”
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